Search results for: Cox regression model
11408 Investigating Elements That Influence Higher Education Institutions’ Digital Maturity
Authors: Zarah M. Bello, Nathan Baddoo, Mariana Lilley, Paul Wernick
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In this paper, we present findings from a multi-part study to evaluate candidate elements reflecting the level of digital capability maturity (DCM) in higher education and the relationship between these elements. We will use these findings to propose a model of DCM for educational institutions. We suggest that the success of learning in higher education is dependent in part on the level of maturity of digital capabilities of institutions as well as the abilities of learners and those who support the learning process. It is therefore important to have a good understanding of the elements that underpin this maturity as well as their impact and interactions in order to better exploit the benefits that technology presents to the modern learning environment and support its continued improvement. Having identified ten candidate elements of digital capability that we believe support the level of a University’s maturity in this area as well as a number of relevant stakeholder roles, we conducted two studies utilizing both quantitative and qualitative research methods. In the first of these studies, 85 electronic questionnaires were completed by various stakeholders in a UK university, with a 100% response rate. We also undertook five in-depth interviews with management stakeholders in the same university. We then utilized statistical analysis to process the survey data and conducted a textual analysis of the interview transcripts. Our findings support our initial identification of candidate elements and support our contention that these elements interact in a multidimensional manner. This multidimensional dynamic suggests that any proposal for improvement in digital capability must reflect the interdependency and cross-sectional relationship of the elements that contribute to DCM. Our results also indicate that the notion of DCM is strongly data-centric and that any proposed maturity model must reflect the role of data in driving maturity and improvement. We present these findings as a key step towards the design of an operationalisable DCM maturity model for universities.Keywords: digital capability, elements, maturity, maturity framework, university
Procedia PDF Downloads 13811407 Sustainability of Green Supply Chain for a Steel Industry Using Mixed Linear Programing Model
Authors: Ameen Alawneh
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The cost of material management across the supply chain represents a major contributor to the overall cost of goods in many companies both manufacturing and service sectors. This fact combined with the fierce competition make supply chains more efficient and cost effective. It also requires the companies to improve the quality of the products and services, increase the effectiveness of supply chain operations, focus on customer needs, reduce wastes and costs across the supply chain. As a heavy industry, steel manufacturing companies in particular are nowadays required to be more environmentally conscious due to their contribution to air, soil, and water pollution that results from emissions and wastes across their supply chains. Steel companies are increasingly looking for methods to reduce or cost cut in the operations and provide extra value to their customers to stay competitive under the current low margins. In this research we develop a green framework model for the sustainability of a steel company supply chain using Mixed integer Linear programming.Keywords: Supply chain, Mixed Integer linear programming, heavy industry, water pollution
Procedia PDF Downloads 44111406 Strategies to Mitigate Disasters at the Hajj Religious Festival Using GIS and Agent Based Modelling
Authors: Muteb Alotaibi, Graham Clarke, Nick Malleson
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The Hajj religious festival at Mina in Saudi Arabia has always presented the opportunity for injuries or deaths. For example, in 1990, a stampede killed 1426 pilgrims, whilst in 1997, 343 people were killed and 1500 injured due to a fire fuelled by high winds sweeping through the tent city in Mina.Many more minor incidents have occurred since then. It is predicted that 5 million pilgrims will soon perform the ritual at Mina (which is, in effect, a temporary city built each year in the desert), which might lead in the future to severe congestion and accidents unless the research is conducted on actions that contribute positively to improving the management of the crowd and facilitating the flow of pilgrims safely and securely. To help prevent further disasters, it is important to first plan better, more accessible locations for emergency services across Mina to ensure a good service for pilgrims. In this paper, we first use a Location Allocation Model (LAM) within a network GIS to examine the optimal locations for key services in the temporary city of Mina. This has been undertaken in relation to the location and movement of the pilgrims during the six day religious festival. The results of various what-if scenarios have been compared against the current location of services. A major argument is that planners should be flexible and locate facilities at different locations throughout the day and night. The use of location-allocation models in this type of comparative static mode has rarely been operationalised in the literature. Second, we model pilgrim movements and behaviours along with the most crowded parts of the network. This has been modelled using an agent-based model. This model allows planners to understand the key bottlenecks in the network and at what usage levels the paths become critically congested. Thus the paper has important implications and recommendations for future disaster planning strategies. This will enable planners to see at what stage in the movements of pilgrims problems occur in terms of potential crushes and trampling incidents. The main application of this research was only customised for pedestrians as the concentration only for pedestrians who move to Jamarat via foot. Further, the network in the middle of Mina was only dedicated for pedestrians for safety, so no Buses, trains and private cars were allowed in this area to prevent the congestion within this network. Initially, this research focus on Mina city as ‘temporary city’ and also about service provision in temporary cities, which is not highlighted in literature so far. Further, it is the first study which use the dynamic demand to optimise the services in the case of day and night time. Moreover, it is the first study which link the location allocation model for optimising services with ABM to find out whether or not the service location is located in the proper location in which it’s not affecting on crowd movement in mainstream flow where some pilgrims need to have health services.Keywords: ABM, crowd management, hajj, temporary city
Procedia PDF Downloads 11511405 Evaluation of Fusion Sonar and Stereo Camera System for 3D Reconstruction of Underwater Archaeological Object
Authors: Yadpiroon Onmek, Jean Triboulet, Sebastien Druon, Bruno Jouvencel
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The objective of this paper is to develop the 3D underwater reconstruction of archaeology object, which is based on the fusion between a sonar system and stereo camera system. The underwater images are obtained from a calibrated camera system. The multiples image pairs are input, and we first solve the problem of image processing by applying the well-known filter, therefore to improve the quality of underwater images. The features of interest between image pairs are selected by well-known methods: a FAST detector and FLANN descriptor. Subsequently, the RANSAC method is applied to reject outlier points. The putative inliers are matched by triangulation to produce the local sparse point clouds in 3D space, using a pinhole camera model and Euclidean distance estimation. The SFM technique is used to carry out the global sparse point clouds. Finally, the ICP method is used to fusion the sonar information with the stereo model. The final 3D models have a précised by measurement comparing with the real object.Keywords: 3D reconstruction, archaeology, fusion, stereo system, sonar system, underwater
Procedia PDF Downloads 29011404 Numerical Investigation for External Strengthening of Dapped-End Beams
Authors: A. Abdel-Moniem, H. Madkour, K. Farah, A. Abdullah
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The reduction in dapped end beams depth nearby the supports tends to produce stress concentration and hence results in shear cracks, if it does not have an adequate reinforcement detailing. This study investigates numerically the efficiency of applying different external strengthening techniques to the dapped end of such beams. A two-dimensional finite element model was built to predict the structural behavior of dapped ends strengthened with different techniques. The techniques included external bonding of the steel angle at the re-entrant corner, un-bounded bolt anchoring, external steel plate jacketing, exterior carbon fiber wrapping and/or stripping and external inclined steel plates. The FE analysis results are then presented in terms of the ultimate load capacities, load-deflection and crack pattern at failure. The results showed that the FE model, at various stages, was found to be comparable to the available test data. Moreover, it enabled the capture of the failure progress, with acceptable accuracy, which is very difficult in a laboratory test.Keywords: dapped-end beams, finite element, shear failure, strengthening techniques, reinforced concrete, numerical investigation
Procedia PDF Downloads 10811403 Identifying Degradation Patterns of LI-Ion Batteries from Impedance Spectroscopy Using Machine Learning
Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee
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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis
Procedia PDF Downloads 13911402 Optimizing Cell Culture Performance in an Ambr15 Microbioreactor Using Dynamic Flux Balance and Computational Fluid Dynamic Modelling
Authors: William Kelly, Sorelle Veigne, Xianhua Li, Zuyi Huang, Shyamsundar Subramanian, Eugene Schaefer
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The ambr15™ bioreactor is a single-use microbioreactor for cell line development and process optimization. The ambr system offers fully automatic liquid handling with the possibility of fed-batch operation and automatic control of pH and oxygen delivery. With operating conditions for large scale biopharmaceutical production properly scaled down, micro bioreactors such as the ambr15™ can potentially be used to predict the effect of process changes such as modified media or different cell lines. In this study, gassing rates and dilution rates were varied for a semi-continuous cell culture system in the ambr15™ bioreactor. The corresponding changes to metabolite production and consumption, as well as cell growth rate and therapeutic protein production were measured. Conditions were identified in the ambr15™ bioreactor that produced metabolic shifts and specific metabolic and protein production rates also seen in the corresponding larger (5 liter) scale perfusion process. A Dynamic Flux Balance model was employed to understand and predict the metabolic changes observed. The DFB model-predicted trends observed experimentally, including lower specific glucose consumption when CO₂ was maintained at higher levels (i.e. 100 mm Hg) in the broth. A Computational Fluid Dynamic (CFD) model of the ambr15™ was also developed, to understand transfer of O₂ and CO₂ to the liquid. This CFD model predicted gas-liquid flow in the bioreactor using the ANSYS software. The two-phase flow equations were solved via an Eulerian method, with population balance equations tracking the size of the gas bubbles resulting from breakage and coalescence. Reasonable results were obtained in that the Carbon Dioxide mass transfer coefficient (kLa) and the air hold up increased with higher gas flow rate. Volume-averaged kLa values at 500 RPM increased as the gas flow rate was doubled and matched experimentally determined values. These results form a solid basis for optimizing the ambr15™, using both CFD and FBA modelling approaches together, for use in microscale simulations of larger scale cell culture processes.Keywords: cell culture, computational fluid dynamics, dynamic flux balance analysis, microbioreactor
Procedia PDF Downloads 27011401 Analysis of Ozone Episodes in the Forest and Vegetation Areas with Using HYSPLIT Model: A Case Study of the North-West Side of Biga Peninsula, Turkey
Authors: Deniz Sari, Selahattin İncecik, Nesimi Ozkurt
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Surface ozone, which named as one of the most critical pollutants in the 21th century, threats to human health, forest and vegetation. Specifically, in rural areas surface ozone cause significant influences on agricultural productions and trees. In this study, in order to understand to the surface ozone levels in rural areas we focus on the north-western side of Biga Peninsula which covers by the mountainous and forested area. Ozone concentrations were measured for the first time with passive sampling at 10 sites and two online monitoring stations in this rural area from 2013 and 2015. Using with the daytime hourly O3 measurements during light hours (08:00–20:00) exceeding the threshold of 40 ppb over the 3 months (May, June and July) for agricultural crops, and over the six months (April to September) for forest trees AOT40 (Accumulated hourly O3 concentrations Over a Threshold of 40 ppb) cumulative index was calculated. AOT40 is defined by EU Directive 2008/50/EC to evaluate whether ozone pollution is a risk for vegetation, and is calculated by using hourly ozone concentrations from monitoring systems. In the present study, we performed the trajectory analysis by The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to follow the long-range transport sources contributing to the high ozone levels in the region. The ozone episodes observed between 2013 and 2015 were analysed using the HYSPLIT model developed by the NOAA-ARL. In addition, the cluster analysis is used to identify homogeneous groups of air mass transport patterns can be conducted through air trajectory clustering by grouping similar trajectories in terms of air mass movement. Backward trajectories produced for 3 years by HYSPLIT model were assigned to different clusters according to their moving speed and direction using a k-means clustering algorithm. According to cluster analysis results, northerly flows to study area cause to high ozone levels in the region. The results present that the ozone values in the study area are above the critical levels for forest and vegetation based on EU Directive 2008/50/EC.Keywords: AOT40, Biga Peninsula, HYSPLIT, surface ozone
Procedia PDF Downloads 24511400 A Critical Exploration of Dominant Perspectives Regarding Inclusion and Disability: Shifts Toward Meaningful Approaches
Authors: Luigi Iannacci
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This study critically explores how disability and disability are presently and problematically configured within education. As such, pedagogies, discourses, and practices that shape this configuration are examined to forward a reconceptualization of disability as it relates to education and the inclusion of students with special needs in mainstream classroom contexts. The study examines how the dominant medical/deficit model of disability positions students with special needs and advocates for a shift towards a social/critical model of disability as applied to education and classrooms. This is demonstrated through a critical look at how language, processes, and ‘interventions’ name and address deficits people who have a disability are presumed to have and, as such, conceptualize these deficits as inherent flaws that are in need of ‘fixing.’ The study will demonstrate the necessary shifts in thinking, language and practice required to forward a critical/social model of disability. The ultimate aim of this research is to offer a much-needed reconceptualization of inclusion that recognizes disability as epistemology, identity, and diversity through a critical exploration of dominant discourses that impact language, policy, instruction and ultimately, the experiences students with disabilities have within mainstream classrooms. The presentation seeks to explore disability as neurodiversity and therefore elucidate how people with disabilities can demonstrate these ways of knowing within inclusive education that avoids superficial approaches that are not responsive to their needs. This research is, therefore, of interest and use to educators teaching at the elementary, secondary, and in-service levels as well as graduate students and scholars working in the areas of inclusion, special education, and literacy. Ultimately the presentation attempts to foster a social justice and human rights-focused approach to inclusion that is responsive to students with disabilities and, as such ensures a reconceptualization of present language, understandings and practices that continue to configure disability in problematic ways.Keywords: inclusion, disability, critical approach, social justice
Procedia PDF Downloads 6711399 Genetic and Non-Genetic Factors Affecting the Response to Clopidogrel Therapy
Authors: Snezana Mugosa, Zoran Todorovic, Zoran Bukumiric, Ivan Radosavljevic, Natasa Djordjevic
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Introduction: Various studies have shown that the frequency of clopidogrel resistance ranges from 4-40%. The aim of this study was to provide in depth analysis of genetic and non-genetic factors that influence clopidogrel resistance in cardiology patients. Methods: We have conducted a prospective study in 200 hospitalized patients hospitalized at Cardiology Centre of the Clinical Centre of Montenegro. CYP2C19 genetic testing was conducted, and the PREDICT score was calculated in 102 out of 200 patients treated with clopidogrel in order to determine the influence of genetic and non-genetic factors on outcomes of interest. Adverse cardiovascular events and adverse reactions to clopidogrel were assessed during 12 months follow up period. Results: PREDICT score and CYP2C19 enzymatic activity were found to be statistically significant predictors of expressing lack of therapeutic efficacy of clopidogrel by multivariate logistic regression, without multicollinearity or interaction between the predictors (p = 0.002 and 0.009, respectively). Conclusions: Pharmacogenetics analyses that were done in the Montenegrin population of patients for the first time suggest that these analyses can predict patient response to the certain therapy. Stepwise approach could be used in assessing the clopidogrel resistance in cardiology patients, combining the PREDICT score, platelet aggregation test, and genetic testing for CYP2C19 polymorphism.Keywords: clopidogrel, pharmacogenetics, pharmacotherapy, PREDICT score
Procedia PDF Downloads 33911398 Discrete-Event Modeling and Simulation Methodologies: Past, Present and Future
Authors: Gabriel Wainer
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Modeling and Simulation methods have been used to better analyze the behavior of complex physical systems, and it is now common to use simulation as a part of the scientific and technological discovery process. M&S advanced thanks to the improvements in computer technology, which, in many cases, resulted in the development of simulation software using ad-hoc techniques. Formal M&S appeared in order to try to improve the development task of very complex simulation systems. Some of these techniques proved to be successful in providing a sound base for the development of discrete-event simulation models, improving the ease of model definition and enhancing the application development tasks; reducing costs and favoring reuse. The DEVS formalism is one of these techniques, which proved to be successful in providing means for modeling while reducing development complexity and costs. DEVS model development is based on a sound theoretical framework. The independence of M&S tasks made possible to run DEVS models on different environments (personal computers, parallel computers, real-time equipment, and distributed simulators) and middleware. We will present a historical perspective of discrete-event M&S methodologies, showing different modeling techniques. We will introduce DEVS origins and general ideas, and compare it with some of these techniques. We will then show the current status of DEVS M&S, and we will discuss a technological perspective to solve current M&S problems (including real-time simulation, interoperability, and model-centered development techniques). We will show some examples of the current use of DEVS, including applications in different fields. We will finally show current open topics in the area, which include advanced methods for centralized, parallel or distributed simulation, the need for real-time modeling techniques, and our view in these fields.Keywords: modeling and simulation, discrete-event simulation, hybrid systems modeling, parallel and distributed simulation
Procedia PDF Downloads 31211397 Assessment of Impact of Urbanization in High Mountain Urban Watersheds
Authors: D. M. Rey, V. Delgado, J. Zambrano Nájera
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Increases in urbanization during XX century, has produced changes in natural dynamics of the basins, which has resulted in increases in runoff volumes, peak flows and flow velocities, that in turn increases flood risk. Higher runoff volumes decrease sewerage networks hydraulic capacity and can cause its failure. This in turn generates increasingly recurrent floods causing mobility problems and general economic detriment in the cities. In Latin America, especially Colombia, this is a major problem because urban population at late XX century was more than 70% is in urban areas increasing approximately in 790% in 1940-1990 period. Besides, high slopes product of Andean topography and high precipitation typical of tropical climates increases velocities and volumes even more, causing stopping of cities during storms. Thus, it becomes very important to know hydrological behavior of Andean Urban Watersheds. This research aims to determine the impact of urbanization in high sloped urban watersheds in its hydrology. To this end, it will be used as study area experimental urban watershed named Palogrande-San Luis watershed, located in the city of Manizales, Colombia. Manizales is a city in central western Colombia, located in Colombian Central Mountain Range (part of Los Andes Mountains) with an abrupt topography (average altitude is 2.153 m). The climate in Manizales is quite uniform, but due to its high altitude it presents high precipitations (1.545 mm/year average) with high humidity (83% average). It was applied HEC-HMS Hydrologic model on the watershed. The inputs to the model were derived from Geographic Information Systems (GIS) theme layers of the Instituto de Estudios Ambientales –IDEA of Universidad Nacional de Colombia, Manizales (Institute of Environmental Studies) and aerial photography taken for the research in conjunction with available literature and look up tables. Rainfall data from a network of 4 rain gages and historical stream flow data were used to calibrate and validate runoff depth using the hydrologic model. Manual calibration was made, and the simulation results show that the model selected is able to characterize the runoff response of the watershed due to land use for urbanization in high mountain watersheds.Keywords: Andean watersheds modelling, high mountain urban hydrology, urban planning, hydrologic modelling
Procedia PDF Downloads 22611396 Proposed Algorithms to Assess Concussion Potential in Rear-End Motor Vehicle Collisions: A Meta-Analysis
Authors: Rami Hashish, Manon Limousis-Gayda, Caitlin McCleery
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Introduction: Mild traumatic brain injuries, also referred to as concussions, represent an increasing burden to society. Due to limited objective diagnostic measures, concussions are diagnosed by assessing subjective symptoms, often leading to disputes to their presence. Common biomechanical measures associated with concussion are high linear and/or angular acceleration to the head. With regards to linear acceleration, approximately 80g’s has previously been shown to equate with a 50% probability of concussion. Motor vehicle collisions (MVCs) are a leading cause of concussion, due to high head accelerations experienced. The change in velocity (delta-V) of a vehicle in an MVC is an established metric for impact severity. As acceleration is the rate of delta-V with respect to time, the purpose of this paper is to determine the relation between delta-V (and occupant parameters) with linear head acceleration. Methods: A meta-analysis was conducted for manuscripts collected using the following keywords: head acceleration, concussion, brain injury, head kinematics, delta-V, change in velocity, motor vehicle collision, and rear-end. Ultimately, 280 studies were surveyed, 14 of which fulfilled the inclusion criteria as studies investigating the human response to impacts, reporting head acceleration, and delta-V of the occupant’s vehicle. Statistical analysis was conducted with SPSS and R. The best fit line analysis allowed for an initial understanding of the relation between head acceleration and delta-V. To further investigate the effect of occupant parameters on head acceleration, a quadratic model and a full linear mixed model was developed. Results: From the 14 selected studies, 139 crashes were analyzed with head accelerations and delta-V values ranging from 0.6 to 17.2g and 1.3 to 11.1 km/h, respectively. Initial analysis indicated that the best line of fit (Model 1) was defined as Head Acceleration = 0.465Keywords: acceleration, brain injury, change in velocity, Delta-V, TBI
Procedia PDF Downloads 21611395 Potential Effects of Climate Change on Streamflow, Based on the Occurrence of Severe Floods in Kelantan, East Coasts of Peninsular Malaysia River Basin
Authors: Muhd. Barzani Gasim, Mohd. Ekhwan Toriman, Mohd. Khairul Amri Kamarudin, Azman Azid, Siti Humaira Haron, Muhammad Hafiz Md. Saad
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Malaysia is a country in Southeast Asia that constantly exposed to flooding and landslide. The disaster has caused some troubles such loss of property, loss of life and discomfort of people involved. This problem occurs as a result of climate change leading to increased stream flow rate as a result of disruption to regional hydrological cycles. The aim of the study is to determine hydrologic processes in the east coasts of Peninsular Malaysia, especially in Kelantan Basin. Parameterized to account for the spatial and temporal variability of basin characteristics and their responses to climate variability. For hydrological modeling of the basin, the Soil and Water Assessment Tool (SWAT) model such as relief, soil type, and its use, and historical daily time series of climate and river flow rates are studied. The interpretation of Landsat map/land uses will be applied in this study. The combined of SWAT and climate models, the system will be predicted an increase in future scenario climate precipitation, increase in surface runoff, increase in recharge and increase in the total water yield. As a result, this model has successfully developed the basin analysis by demonstrating analyzing hydrographs visually, good estimates of minimum and maximum flows and severe floods observed during calibration and validation periods.Keywords: east coasts of Peninsular Malaysia, Kelantan river basin, minimum and maximum flows, severe floods, SWAT model
Procedia PDF Downloads 25411394 Environmental Effect of Empty Nest Households in Germany: An Empirical Approach
Authors: Dominik Kowitzke
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Housing constructions have direct and indirect environmental impacts especially caused by soil sealing and gray energy consumption related to the use of construction materials. Accordingly, the German government introduced regulations limiting additional annual soil sealing. At the same time, in many regions like metropolitan areas the demand for further housing is high and of current concern in the media and politics. It is argued that meeting this demand by making better use of the existing housing supply is more sustainable than the construction of new housing units. In this context, targeting the phenomenon of so-called over the housing of empty nest households seems worthwhile to investigate for its potential to free living space and thus, reduce the need for new housing constructions and related environmental harm. Over housing occurs if no space adjustment takes place in household lifecycle stages when children move out from home and the space formerly created for the offspring is from then on under-utilized. Although in some cases the housing space consumption might actually meet households’ equilibrium preferences, frequently space-wise adjustments to the living situation doesn’t take place due to transaction or information costs, habit formation, or government intervention leading to increasing costs of relocations like real estate transfer taxes or tenant protection laws keeping tenure rents below the market price. Moreover, many detached houses are not long-term designed in a way that freed up space could be rent out. Findings of this research based on socio-economic survey data, indeed, show a significant difference between the living space of empty nest and a comparison group of households which never had children. The approach used to estimate the average difference in living space is a linear regression model regressing the response variable living space on a two-dimensional categorical variable distinguishing the two groups of household types and further controls. This difference is assumed to be the under-utilized space and is extrapolated to the total amount of empty nests in the population. Supporting this result, it is found that households that move, despite market frictions impairing the relocation, after children left their home tend to decrease the living space. In the next step, only for areas with tight housing markets in Germany and high construction activity, the total under-utilized space in empty nests is estimated. Under the assumption of full substitutability of housing space in empty nests and space in new dwellings in these locations, it is argued that in a perfect market with empty nest households consuming their equilibrium demand quantity of housing space, dwelling constructions in the amount of the excess consumption of living space could be saved. This, on the other hand, would prevent environmental harm quantified in carbon dioxide equivalence units related to average constructions of detached or multi-family houses. This study would thus provide information on the amount of under-utilized space inside dwellings which is missing in public data and further estimates the external effect of over housing in environmental terms.Keywords: empty nests, environment, Germany, households, over housing
Procedia PDF Downloads 16611393 Design Evaluation Tool for Small Wind Turbine Systems Based on the Simple Load Model
Authors: Jihane Bouabid
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The urgency to transition towards sustainable energy sources has revealed itself imperative. Today, in the 21st Century, the intellectual society have imposed technological advancements and improvements, and anticipates expeditious outcomes as an integral component of its relentless pursuit of an elevated standard of living. As a part of empowering human development, driving economic growth and meeting social needs, the access to energy services has become a necessity. As a part of these improvements, we are introducing the project "Mywindturbine" - an interactive web user interface for design and analysis in the field of wind energy, with a particular adherence to the IEC (International Electrotechnical Commission) standard 61400-2 "Wind turbines – Part 2: Design requirements for small wind turbines". Wind turbines play a pivotal role in Morocco's renewable energy strategy, leveraging the nation's abundant wind resources. The IEC 61400-2 standard ensures the safety and design integrity of small wind turbines deployed in Morocco, providing guidelines for performance and safety protocols. The conformity with this standard ensures turbine reliability, facilitates standards alignment, and accelerates the integration of wind energy into Morocco's energy landscape. The aim of the GUI (Graphical User Interface) for engineers and professionals from the field of wind energy systems who would like to design a small wind turbine system following the safety requirements of the international standards IEC 61400-2. The interface provides an easy way to analyze the structure of the turbine machine under normal and extreme load conditions based on the specific inputs provided by the user. The platform introduces an overview to sustainability and renewable energy, with a focus on wind turbines. It features a cross-examination of the input parameters provided from the user for the SLM (Simple Load Model) of small wind turbines, and results in an analysis according to the IEC 61400-2 standard. The analysis of the simple load model encompasses calculations for fatigue loads on blades and rotor shaft, yaw error load on blades, etc. for the small wind turbine performance. Through its structured framework and adherence to the IEC standard, "Mywindturbine" aims to empower professionals, engineers, and intellectuals with the knowledge and tools necessary to contribute towards a sustainable energy future.Keywords: small wind turbine, IEC 61400-2 standard, user interface., simple load model
Procedia PDF Downloads 4911392 Modeling Socioeconomic and Political Dynamics of Terrorism in Pakistan
Authors: Syed Toqueer, Omer Younus
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Terrorism, today, has emerged as a global menace with Pakistan being the most adversely affected state. Therefore, the motive behind this study is to empirically establish the linkage of terrorism with socio-economic (uneven income distribution, poverty and unemployment) and political nexuses so that a policy recommendation can be put forth to better approach this issue in Pakistan. For this purpose, the study employs two competing models, namely, the distributed lag model and OLS, so that findings of the model may be consolidated comprehensively, over the reference period of 1984-2012. The findings of both models are indicative of the fact that uneven income distribution of Pakistan is rather a contributing factor towards terrorism when measured through GDP per capita. This supports the hypothesis that immiserizing modernization theory is applicable for the state of Pakistan where the underprivileged are marginalized. Results also suggest that other socio-economic variables (poverty, unemployment and consumer confidence) can condense the brutality of terrorism once these conditions are catered to and improved. The rational of opportunity cost is at the base of this argument. Poor conditions of employment and poverty reduces the opportunity cost for individuals to be recruited by terrorist organizations as economic returns are considerably low and thus increasing the supply of volunteers and subsequently increasing the intensity of terrorism. The argument of political freedom as a means of lowering terrorism stands true. The more the people are politically repressed the more alternative and illegal means they will find to make their voice heard. Also, the argument that politically transitioning economy faces more terrorism is found applicable for Pakistan. Finally, the study contributes to an ongoing debate on which of the two set of factors are more significant with relation to terrorism by suggesting that socio-economic factors are found to be the primary causes of terrorism for Pakistan.Keywords: terrorism, socioeconomic conditions, political freedom, distributed lag model, ordinary least square
Procedia PDF Downloads 31511391 The Effects of Displacer-Cylinder-Wall Conditions on the Performance of a Medium-Temperature-Differential γ-Type Stirling Engine
Authors: Wen-Lih Chen, Chao-Kuang Chen, Mao-Ju Fang, Hsiang-Cheng Hsu
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In this study, we conducted CFD simulation to study the gas cycle of a medium-temperature-differential (MTD) γ-type Stirling engine. Mesh compression and expansion as well as overset mesh techniques are employed to simulate the moving parts of the engine. Shear-Stress Transport (SST) k-ω turbulence model has been adopted because the model is not prone to generate excessive turbulence upon impingement regions. Hence, wall heat transfer rates at the hot and cold ends will not be overestimated. The effects of several different displacer-cylinder-wall temperature setups, including smooth and finned walls, on engine performance are investigated. The results include temperature contours, pressure versus volume diagrams, and variations of heat transfer rates, indicated power, and efficiency. It is found that displacer-wall heat transfer is one of the most important factors on engine performance, and some wall-temperature setups produce better results than others.Keywords: CFD, finned wall, MTD Stirling engine, heat transfer
Procedia PDF Downloads 36411390 An Optimal Control Method for Reconstruction of Topography in Dam-Break Flows
Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid
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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil
Procedia PDF Downloads 12511389 Long-Range Transport of Biomass Burning Aerosols over South America: A Case Study in the 2019 Amazon Rainforest Wildfires Season
Authors: Angel Liduvino Vara-Vela, Dirceu Luis Herdies, Debora Souza Alvim, Eder Paulo Vendrasco, Silvio Nilo Figueroa, Jayant Pendharkar, Julio Pablo Reyes Fernandez
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Biomass-burning episodes are quite common in the central Amazon rainforest and represent a dominant source of aerosols during the dry season, between August and October. The increase in the occurrence of fires in 2019 in the world’s largest biomes has captured the attention of the international community. In particular, a rare and extreme smoke-related event occurred in the afternoon of Monday, August 19, 2019, in the most populous city in the Western Hemisphere, the São Paulo Metropolitan Area (SPMA), located in southeastern Brazil. The sky over the SPMA suddenly blackened, with the day turning into night, as reported by several news media around the world. In order to clarify whether or not the smoke that plunged the SPMA into sudden darkness was related to wildfires in the Amazon rainforest region, a set of 48-hour simulations over South America were performed using the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 20 km horizontal resolution, on a daily basis, during the period from August 16 to August 19, 2019. The model results were satisfactorily compared against satellite-based data products and in situ measurements collected from air quality monitoring sites. Although a very strong smoke transport coming from the Amazon rainforest was observed in the middle of the afternoon on August 19, its impact on air quality over the SPMA took place in upper levels far above the surface, where, conversely, low air pollutant concentrations were observed.Keywords: Amazon rainforest, biomass burning aerosols, São Paulo metropolitan area, WRF-Chem model
Procedia PDF Downloads 12811388 Mitigating Climate Change: Cross-Country Variation in Policy Ambition
Authors: Mohammad Aynal Haque
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Under the international cooperation — Paris Agreement — countries outline their self-determined policy ambition for emissions reduction in their Nationally Determined Contributions (NDCs) as a key to addressing climate change globally. Although practically all countries commit themselves to reach the Paris landmark (below 20 C) globally, some act as climate leaders, others behave as followers, and others turn out to be climate laggards. As a result, there is a substantial variation in ‘emissions reduction targets’ across countries. Thus, a question emerges: What explains this variation? Or why do some countries opt for higher while others opt for lower ‘emissions reduction targets toward global mitigation efforts? Conceptualizing the ‘emissions reduction targets by 2030’ outlined in NDCs by each country as the climate policy ambition (CPA), this paper explores how certain national political, economic, environmental, and external factors play vital roles in determining climate policy ambition. Based on the cross-country regression analysis among 168 countries, this study finds that democracy, vulnerability to climate change effects, and foreign direct investment have substantial effects on CPA. The paper also finds that resource capacity has a minimal negative effect on CPA across developed countries.Keywords: climate change, Paris agreement, international cooperation, political economy, environmental politics, NDCs
Procedia PDF Downloads 6711387 Self-Efficacy, Self-Knowledge, Empathy and Psychological Well-Being as Predictors of Workers’ Job Performance in Food and Beverage Industries in the South-West, Nigeria
Authors: Michael Ayodeji Boyede
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Studies have shown that workers’ job performance is very low in Nigeria, especially in the food and beverage industry. This trend had been partially attributed to low workers’ self-efficacy, poor self-knowledge, lack of empathy and poor psychological well-being. The descriptive survey design was adopted. Four factories were purposively selected from three states in Southwestern, Nigeria (Lagos, Ogun and Oyo States). Proportionate random sampling techniques were used in selecting 1,820 junior and supervisory cadre workers in Nestle Plc (369), Coca-Cola Plc (392), Cadbury Plc (443) and Nigeria Breweries (616). The five research instruments used were: Workers’ self-efficacy (r=0.81), Workers’ self-knowledge (r=0.78), Workers’ empathy (r=0.74), Workers’ psychological well-being (r=0.70) and Workers’ performance rating (r=0.72) scales. Quantitative data were analysed using Pearson product moment correlation, Multiple regression at 0.05 level of significance. Findings show that there were significant relationships between Workers’ job performance and self-efficacy (r=.56), self-knowledge (r=.54), Empathy (r=.55) and Psychological Well-being (r=.69) respectively. Self-efficacy, self-knowledge, empathy and psychological well-being jointly predict workers’ job performance (F (4,1815) = 491.05) accounting for 52.0% of its variance. Psychological well-being (B=.52). Self-efficacy (B=.10), self-knowledge (B=.11), empathy (B=. 09) had predictive relative weights on workers’ job performance. Inadequate knowledge and training of the supervisors led to a mismatch of workers thereby reducing workers’ job performance. High self-efficacy, empathy, psychological well-being and good self-knowledge influence workers job performance in the food and beverage industry. Based on the finding employers of labour should provide work environment that would enhance and promote the development of these factors among the workers.Keywords: self-efficacy, self-knowledge, empathy, psychological well-being, job performance
Procedia PDF Downloads 25011386 Integrating Virtual Reality and Building Information Model-Based Quantity Takeoffs for Supporting Construction Management
Authors: Chin-Yu Lin, Kun-Chi Wang, Shih-Hsu Wang, Wei-Chih Wang
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A construction superintendent needs to know not only the amount of quantities of cost items or materials completed to develop a daily report or calculate the daily progress (earned value) in each day, but also the amount of quantities of materials (e.g., reinforced steel and concrete) to be ordered (or moved into the jobsite) for performing the in-progress or ready-to-start construction activities (e.g., erection of reinforced steel and concrete pouring). These daily construction management tasks require great effort in extracting accurate quantities in a short time (usually must be completed right before getting off work every day). As a result, most superintendents can only provide these quantity data based on either what they see on the site (high inaccuracy) or the extraction of quantities from two-dimension (2D) construction drawings (high time consumption). Hence, the current practice of providing the amount of quantity data completed in each day needs improvement in terms of more accuracy and efficiency. Recently, a three-dimension (3D)-based building information model (BIM) technique has been widely applied to support construction quantity takeoffs (QTO) process. The capability of virtual reality (VR) allows to view a building from the first person's viewpoint. Thus, this study proposes an innovative system by integrating VR (using 'Unity') and BIM (using 'Revit') to extract quantities to support the above daily construction management tasks. The use of VR allows a system user to be present in a virtual building to more objectively assess the construction progress in the office. This VR- and BIM-based system is also facilitated by an integrated database (consisting of the information and data associated with the BIM model, QTO, and costs). In each day, a superintendent can work through a BIM-based virtual building to quickly identify (via a developed VR shooting function) the building components (or objects) that are in-progress or finished in the jobsite. And he then specifies a percentage (e.g., 20%, 50% or 100%) of completion of each identified building object based on his observation on the jobsite. Next, the system will generate the completed quantities that day by multiplying the specified percentage by the full quantities of the cost items (or materials) associated with the identified object. A building construction project located in northern Taiwan is used as a case study to test the benefits (i.e., accuracy and efficiency) of the proposed system in quantity extraction for supporting the development of daily reports and the orders of construction materials.Keywords: building information model, construction management, quantity takeoffs, virtual reality
Procedia PDF Downloads 12511385 Parameterized Lyapunov Function Based Robust Diagonal Dominance Pre-Compensator Design for Linear Parameter Varying Model
Authors: Xiaobao Han, Huacong Li, Jia Li
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For dynamic decoupling of linear parameter varying system, a robust dominance pre-compensator design method is given. The parameterized pre-compensator design problem is converted into optimal problem constrained with parameterized linear matrix inequalities (PLMI); To solve this problem, firstly, this optimization problem is equivalently transformed into a new form with elimination of coupling relationship between parameterized Lyapunov function (PLF) and pre-compensator. Then the problem was reduced to a normal convex optimization problem with normal linear matrix inequalities (LMI) constraints on a newly constructed convex polyhedron. Moreover, a parameter scheduling pre-compensator was achieved, which satisfies robust performance and decoupling performances. Finally, the feasibility and validity of the robust diagonal dominance pre-compensator design method are verified by the numerical simulation of a turbofan engine PLPV model.Keywords: linear parameter varying (LPV), parameterized Lyapunov function (PLF), linear matrix inequalities (LMI), diagonal dominance pre-compensator
Procedia PDF Downloads 39311384 Investigation of Dissolution in Diammonium Hydrogen Phosphate Solutions of Gypsum
Authors: Turan Çalban, Nursel Keskin, Sabri Çolak, Soner Kuşlu
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Gypsum (CaSO4.2H2O) is a mineral that is found in large quantities in the Turkey and in the World. The dissolution of this mineral in the diammonium hydrogen phosphate solutions has not been studied so far. Investigation of the dissolution and dissolution kinetics gypsum in diammonium hydrogen phosphate solutions will be useful for evaluating of solid wastes containing gypsum. In this study, parameters such as diammonium hydrogen phosphate concentration, temperature and stirring speed affecting on the dissolution rate of the gypsum in diammonium hydrogen phosphate solutions were investigated. In experimental studies have researched effectiveness of the selected parameters. The dissolution of gypsum were examined in two parts at low and high temperatures. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solid-fluid systems. The activation energy was found to be 34.58 kJ/mol and 44.45 kJ/mol for the low and the high temperatures. The dissolution of gypsum was controlled by chemical reaction both low temperatures and high temperatures. Reaction rate expressions of dissolution of gypsum at the low temperatures and the high temperatures controlled by chemical reaction are as follows, respectively. = k1.e-5159.5/T.t = k2.e-5346.8/T.t Where k1 and k2 are constants depending on the diammonium hydrogen phosphate solution concentration, the solid/liquid ratio, the stirring speed and the particle size.Keywords: diammonium hydrogen phosphate, dissolution kinetics, gypsum, kinetics.
Procedia PDF Downloads 37611383 Collision Detection Algorithm Based on Data Parallelism
Authors: Zhen Peng, Baifeng Wu
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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.Keywords: data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability
Procedia PDF Downloads 28111382 Ground Surface Temperature History Prediction Using Long-Short Term Memory Neural Network Architecture
Authors: Venkat S. Somayajula
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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical featuresKeywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle
Procedia PDF Downloads 12011381 Development and Validation of a HPLC Method for 6-Gingerol and 6-Shogaol in Joint Pain Relief Gel Containing Ginger (Zingiber officinale)
Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed.
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High-Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20-60 and 6-18 µg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 µg/ml and for 6S were 0.3672 and 1.2238 µg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.Keywords: ginger, 6-gingerol, HPLC, 6-shogaol
Procedia PDF Downloads 43111380 Socio-Economic Factors Influencing the Use of Coping Strategies among Conflict Actors (Farmers and Herders) in Giron Masa Village, Kebbi State, Nigeria
Authors: S. Umar, B. F. Umar
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This study was conducted at Giron Masa village, located 30 km from Yauri town. The study determines the socio-economic factors influencing the use of coping strategies among farmers and herders during post-conflict situation. Simple random sampling was employed to select one hundred respondents (50 farmers and 50 herders) from the study area. Logistic regression analysis (LR) was used to ascertain the socioeconomic variables that influenced the use of the coping strategies. The results of the study shows that age, income, family size and farming experience were individually significant and thus influenced the use of POCS by farmers. Annual income and production system influenced the use of POCS by herders. Age, farm size and farming experience were found to be individually significant in influencing the use of EOCS among farmers. Specifically, years of occupation experience among the herders increased the use of emotion oriented coping strategies among herders. The use of SSCS among farmers was influenced by educational level; farm size and farming experience, while the variables are not collectively significant in influencing the use of SSCS among the herders. The research recommends a need to adopt the strategy of community coping to cope with stress.Keywords: farmers, herders, conflict, coping strategies
Procedia PDF Downloads 36011379 Application Methodology for the Generation of 3D Thermal Models Using UAV Photogrammety and Dual Sensors for Mining/Industrial Facilities Inspection
Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón
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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. Unmanned Aerial Vehicle (UAV) techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. A methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of visible Red-Blue-Green (RGB) and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.Keywords: aerial thermography, data processing, drone, low-cost, point cloud
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